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  2. Faculty of Information and Communication Technology
  3. Department of Artificial Intelligence
  4. Dissertations - FacICTAI
  5. Dissertations - FacICTAI - 2002-2014
Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/78581
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dc.date.accessioned2021-07-23T09:07:11Z-
dc.date.available2021-07-23T09:07:11Z-
dc.date.issued2011-
dc.identifier.citationGyawali, B. (2001) Answering factoid questions via Ontologies : a natural language generation approach (Master's dissertation).en_GB
dc.identifier.urihttps://www.um.edu.mt/library/oar/handle/123456789/78581-
dc.descriptionM.SC.LANG.SCIENCE&TECH.en_GB
dc.description.abstractWe present a systematic approach to the generation of natural language descriptions of logical facts from ontologies. We design and discuss our Natural Language Generation (NLG) architecture in terms of implementing a factoid question answer platform upon ontologies; who identify what questions can be asked upon the knowledge base, determine relevant contents from the knowledge base that best serve generating response to the questions and process those contents confirming to the popular patterns of expression, as identified from a survey, in order to generate answers in natural language (English); all of this while justifying the rationale of the approach and the possible benefits such systems can offer.en_GB
dc.language.isoenen_GB
dc.rightsinfo:eu-repo/semantics/restrictedAccessen_GB
dc.subjectNatural language processing (Computer science)en_GB
dc.subjectArtificial intelligenceen_GB
dc.subjectCognitive scienceen_GB
dc.titleAnswering factoid questions via Ontologies : a natural language generation approachen_GB
dc.typemasterThesisen_GB
dc.rights.holderThe copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder.en_GB
dc.publisher.institutionUniversity of Maltaen_GB
dc.publisher.departmentFaculty of Information and Communication Technology. Department of Artificial Intelligenceen_GB
dc.description.reviewedN/Aen_GB
dc.contributor.creatorGyawali, Bikash (2011)-
Appears in Collections:Dissertations - FacICT - 2011
Dissertations - FacICTAI - 2002-2014

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